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treesnip <a href='https://curso-r.github.io/treesnip'><img src='man/figures/logo.png' align="right" height="139" /></a>

This package provides the following bindings for parsnip package:

the tree engine for decision_tree;
the catboost engine for boost_tree - only available in catboost branch. See catboost;
the lightGBM engine for boost_tree.

Note that the development of this package has shifted to the bonsai package. We suggest filing issues and/or pull requests there.

docs

Installation

Not on CRAN yet.

remotes::install_github("curso-r/treesnip")

See catboost to use with catboost.

Minimal Example

# decision_tree
model <- parsnip::decision_tree()
parsnip::set_engine(model, "tree")

# boost_tree
model <- parsnip::boost_tree(mtry = 1, trees = 50)

parsnip::set_engine(model, "catboost")
parsnip::set_engine(model, "lightgbm")

Hyperparameters map

decision_tree()

<table> <thead> <tr> <th style="text-align:left;"> parsnip </th> <th style="text-align:left;"> tree </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> min_n </td> <td style="text-align:left;"> minsize </td> </tr> <tr> <td style="text-align:left;"> cost_complexity </td> <td style="text-align:left;"> mindev </td> </tr> </tbody> </table>

boost_tree()

<table> <thead> <tr> <th style="text-align:left;"> parsnip </th> <th style="text-align:left;"> catboost </th> <th style="text-align:left;"> lightGBM </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> mtry </td> <td style="text-align:left;"> rsm </td> <td style="text-align:left;"> feature_fraction </td> </tr> <tr> <td style="text-align:left;"> trees </td> <td style="text-align:left;"> iterations </td> <td style="text-align:left;"> num_iterations </td> </tr> <tr> <td style="text-align:left;"> min_n </td> <td style="text-align:left;"> min_data_in_leaf </td> <td style="text-align:left;"> min_data_in_leaf </td> </tr> <tr> <td style="text-align:left;"> tree_depth </td> <td style="text-align:left;"> depth </td> <td style="text-align:left;"> max_depth </td> </tr> <tr> <td style="text-align:left;"> learn_rate </td> <td style="text-align:left;"> learning_rate </td> <td style="text-align:left;"> learning_rate </td> </tr> <tr> <td style="text-align:left;"> loss_reduction </td> <td style="text-align:left;"> <span style=" font-weight: bold; color: red !important;">Not found</span> </td> <td style="text-align:left;"> min_gain_to_split </td> </tr> <tr> <td style="text-align:left;"> sample_size </td> <td style="text-align:left;"> subsample </td> <td style="text-align:left;"> bagging_fraction </td> </tr> </tbody> </table>

Catboost

Originally treesnip had support for both lightgbm and catboost. Since catboost has no intent to make it to CRAN we removed the parsnip implementation from the main package. You can still use it from the catboost branch that we will keep up to date with the main branch.

The catboost branch can be installed with:

remotes::install_github("curso-r/treesnip@catboost")